Automated Deep Learning Artificial Intelligence Tool for Spleen Segmentation on CT: Defining Volume-Based Thresholds for Splenomegaly.

BACKGROUND. Splenomegaly historically has been assessed on imaging by use of potentially inaccurate linear measurements. Prior work tested a deep learning artificial intelligence (AI) tool that automatically segments the spleen to determine splenic volume. OBJECTIVE. The purpose of this study is to apply the deep learning AI tool in a large screening population to establish volume-based splenomegaly thresholds. METHODS. This retrospective study included a primary (screening) sample of 8901 patients (4235 men, 4666 women; mean age, 56 ± 10 [SD] years) who underwent CT colonoscopy (n = 7736) or renal donor CT (n = 1165) from April 2004 to January 2017 and a secondary sample of 104 patients (62 men, 42 women; mean age, 56 ± 8 years) with end-stage liver disease who underwent contrast-enhanced CT performed as part of evaluation for potential liver transplant from January 2011 to May 2013. The automated deep learning AI tool was used for spleen segmentation, to determine splenic volumes. Two radiologists independently reviewed a subset of segmentations. Weight-based volume thresholds for splenomegaly were derived using regression analysis. Performance of linear measurements was assessed. Frequency of splenomegaly in the secondary sample was determined using weight-based volumetric thresholds. RESULTS. In the primary sample, both observers confirmed splenectomy in 20 patients with an automated splenic volume of 0 mL; confirmed incomplete splenic coverage in 28 patients with a tool output error; and confirmed adequate segmentation in 21 patients with low volume (< 50 mL), 49 patients with high volume (> 600 mL), and 200 additional randomly selected patients. In 8853 patients included in analysis of splenic volumes (i.e., excluding a value of 0 mL or error values), the mean automated splenic volume was 216 ± 100 [SD] mL. The weight-based volumetric threshold (expressed in milliliters) for splenomegaly was calculated as (3.01 × weight [expressed as kilograms]) + 127; for weight greater than 125 kg, the splenomegaly threshold was constant (503 mL). Sensitivity and specificity for volume-defined splenomegaly were 13% and 100%, respectively, at a true craniocaudal length of 13 cm, and 78% and 88% for a maximum 3D length of 13 cm. In the secondary sample, both observers identified segmentation failure in one patient. The mean automated splenic volume in the 103 remaining patients was 796 ± 457 mL; 84% (87/103) of patients met the weight-based volume-defined splenomegaly threshold. CONCLUSION. We derived a weight-based volumetric threshold for splenomegaly using an automated AI-based tool. CLINICAL IMPACT. The AI tool could facilitate large-scale opportunistic screening for splenomegaly.

Rapid onset of orbital cellulitis after uncomplicated strabismus surgery.

Orbital cellulitis is extremely uncommon following strabismus surgery. When it occurs, the infection has been reported to present from day 1 to within 1 week following surgery and has the potential for significant morbidity. We report the case of a 6.5-year-old boy presenting with unilateral orbital cellulitis growing group A Streptococcus pyogenes on postoperative day 1, after uncomplicated bilateral medial rectus recessions. The patient had two contacts with streptococcal pharyngitis at the time of surgery but was completely asymptomatic himself. We hypothesize that these contacts may have led to the rapid onset of his orbital cellulitis.

Congenital nasal pyriform aperture stenosis and ocular albinism co-occurring in a sibship with a maternally-inherited 97 kb Xp22.2 microdeletion.

Congenital Nasal Pyriform Aperture Stenosis (CNPAS) is a rare congenital malformation caused by overgrowth of the maxillary bone. We report on two patients, brothers born 3 and 1½ years apart, both presented at birth with radiographically diagnosed CNPAS. Both siblings also were born with ocular albinism, which is known to have X-linked inheritance. Subsequent genetic testing demonstrated a 97 kb deletion in the p arm of the X chromosome in both siblings and their mother. This deletion encompasses a gene known to cause ocular albinism (GPR143), as well as partial deletion of two other genes, TBL1X and SHROOM2. This is the first reported case of CNPAS in siblings, both males, sharing a maternally inherited Xp22.2 deletion.